def test_get_seqs(self):
""" Testing getting the protein sequences from the dataset. """
#1.)
test_pySAR = pysar.PySAR(config_file=self.all_config_files[0])
test_seqs = test_pySAR.get_seqs()
self.assertEqual(test_seqs.shape, (test_pySAR._num_seqs, ),
'Shape of the sequences not correct, expected {}, got {}.'.format(test_seqs.shape, (test_pySAR._num_seqs, )))
self.assertIsInstance(test_seqs, pd.Series,
'Sequences not correct type, expected {}, got {}.'.format(pd.Series, type(test_seqs)))
self.assertTrue(test_seqs[0].startswith("MTIKEMPQPK"),
'Error in first seqeuence, expected it to start with MTIKEMPQPK.')
self.assertEqual(test_seqs.dtype, object,
'Sequence object expected to be of dtype object, got {}.'.format(test_seqs.dtype))
#2.)
test_pySAR_2 = pysar.PySAR(config_file=self.all_config_files[1])
test_seqs = test_pySAR_2.get_seqs()
self.assertEqual(test_seqs.shape, (test_pySAR_2._num_seqs, ),
'Shape of the sequences not correct, expected {}, got {}.'.format(test_seqs.shape, (test_pySAR_2._num_seqs, )))
self.assertIsInstance(test_seqs, pd.Series,
'Sequences not correct type, expected {}, got {}'.format(pd.Series, type(test_seqs)))
self.assertTrue(test_seqs[0].startswith("MSAPFAKF"),
'Error in second seqeuence expected it to start with MSAPFAKF.')
self.assertEqual(test_seqs.dtype, object,
'Sequence object expected to be of dtype object, got {}.'.format(test_seqs.dtype))
#3.)
test_pySAR_3 = pysar.PySAR(config_file=self.all_config_files[2])
test_seqs = test_pySAR_3.get_seqs()
self.assertEqual(test_seqs.shape, (test_pySAR_3._num_seqs, ),
'Shape of the sequences not correct, expected {}, got {}.'.format(test_seqs.shape, (test_pySAR_3._num_seqs, )))
self.assertIsInstance(test_seqs, pd.Series,
'Sequences not correct type, expected {}, got {}'.format(pd.Series, type(test_seqs)))
self.assertTrue(test_seqs[0].startswith("MLMTVFSSAP"),
'Error in third seqeuence expected it to start with MLMTVFSSAP.')
self.assertEqual(test_seqs.dtype, object,
'Sequence object expected to be of dtype object, got {}'.format(test_seqs.dtype))
#4.)
test_pySAR_4 = pysar.PySAR(config_file=self.all_config_files[3])
test_seqs = test_pySAR_4.get_seqs()
self.assertEqual(test_seqs.shape, (test_pySAR_4._num_seqs, ),
'Shape of the sequences not correct, expected {}, got {}.'.format(test_seqs.shape, (test_pySAR_4._num_seqs, )))
self.assertIsInstance(test_seqs, pd.Series,
'Sequences not correct type, expected {}, got {}'.format(pd.Series, type(test_seqs)))
self.assertTrue(test_seqs[0].startswith("MSRLVAASWL"),
'Error in third seqeuence expected it to start with MSRLVAASWL.')
self.assertEqual(test_seqs.dtype, object,
'Sequence object expected to be of dtype object, got {}'.format(test_seqs.dtype))
def test_get_aai_encoding(self):
""" Testing getting the AAI encoding from the database for specific indices. """
aa_indices = ["CHAM810101", "ISOY800103"]
aa_indices1 = "NAKH920102"
error_aaindices = ["ABCD1234", "ABCD12345"]
error_aaindices1 = "XYZ4567"
#1.)
test_pySAR = pysar.PySAR(config_file=self.all_config_files[0])
aai_encoding = test_pySAR.get_aai_encoding(aa_indices)
self.assertIsInstance(aai_encoding, np.ndarray,
'AAI Encoding output expected to be a numpy array, got datatype {}.'.format(type(aai_encoding)))
self.assertEqual(aai_encoding.shape[0], test_pySAR.num_seqs,
'The number of sequences in the dataset expected to be {}, got {}.'.format(test_pySAR.num_seqs, aai_encoding.shape[0]))
self.assertEqual(aai_encoding.shape[1], test_pySAR.seq_len*len(aa_indices),
'The length of the sequences expected to be {}, got {}.'.format(test_pySAR.seq_len, str(aai_encoding.shape[1])))
self.assertEqual(aai_encoding.dtype,np.float32,
'Datatype of elements in numpy array expected be dtype np.float32, got {}.'.format(aai_encoding.dtype))
self.assertTrue((np.array([0.78, 0.5, 1.02, 0.68, 0.68, 0.78, 0.36, 0.68, \
0.36, 0.68], dtype=np.float32)==aai_encoding[0][:10]).all(),
'The first 10 elements of sequence 0 do not match what was expected.')
#2.)
test_pySAR_1 = pysar.PySAR(config_file=self.all_config_files[1])
aai_encoding_1 = test_pySAR_1.get_aai_encoding(aa_indices1)
self.assertIsInstance(aai_encoding_1, np.ndarray,
'AAI Encoding output expected to be a numpy array, got datatype {}.'.format(type(aai_encoding_1)))
self.assertEqual(aai_encoding_1.shape[0], test_pySAR_1.num_seqs,
'The number of sequences in the dataset expected to be {}, got {}.'.format(test_pySAR_1.num_seqs, aai_encoding_1.shape[0]))
self.assertEqual(aai_encoding_1.shape[1], test_pySAR_1.seq_len,
'The length of the sequences expected to be {}, got {}.'.format(test_pySAR_1.seq_len, str(aai_encoding_1.shape[1])))
self.assertEqual(aai_encoding_1.dtype,np.float32,
'Datatype of elements in numpy array should be of dtype np.float32, got {}.'.format(aai_encoding_1.dtype))
# self.assertTrue((np.array([3.79, 3.51, 1.8, 6.11, 9.34, 3.79, 7.21, 4.68, 7.21, \
# 6.11],dtype=np.float32)==aai_encoding_1[0][:10]).all(),
# 'The first 10 elements of sequence 0 do not match what was expected.')
#3.) #testing errenous indices
with self.assertRaises(ValueError, msg='ValueError: Errorneous indices have been input.'):
aai_encoding = test_pySAR_1.get_aai_encoding(error_aaindices)
#4.)
with self.assertRaises(ValueError, msg='ValueError: Errorneous indices have been input.'):
aai_encoding = test_pySAR_1.get_aai_encoding(error_aaindices1)
#5.)
with self.assertRaises(TypeError, msg='TypeError: Errorneous indices datatypes have been input.'):
aai_encoding = test_pySAR_1.get_aai_encoding(1235)
aai_encoding = test_pySAR_1.get_aai_encoding(40.89)
aai_encoding = test_pySAR_1.get_aai_encoding(False)
def test_aai_desc_encoding(self):
""" Testing AAI + Descriptor encoding functionality. """
aa_indices_1 = "CHAM810101"
aa_indices_2 = "NAKH920102"
aa_indices_3 = "LIFS790103"
aa_indices_4 = ["PTIO830101", "QIAN880136", "RACS820110"]
desc_1 = "aa_comp"
desc_2 = "distribution"
desc_3 = "conjoint_triad"
desc_4 = ["moranauto", "quasi_seq_order"]
test_pySAR = pysar.PySAR(config_file=self.all_config_files[0])
#1.)
with self.assertRaises(ValueError, msg='ValueError: Descriptor and indices parameter cannot both be None.'):
test_desc = test_pySAR.encode_desc(descriptor=None)
test_desc = test_pySAR.encode_aai_desc(indices=None)
test_desc = test_pySAR.encode_aai_desc(descriptor="aa_comp")
test_desc = test_pySAR.encode_aai_desc(indices="LIFS790103")
#2.)
with self.assertRaises(ValueError, msg='ValueError: Descriptor and indices must be lists or strings.'):
test_desc = test_pySAR.encode_desc(descriptor=123)
test_desc = test_pySAR.encode_aai_desc(indices=0.90)
test_desc = test_pySAR.encode_aai_desc(descriptor=False)
test_desc = test_pySAR.encode_aai_desc(indices=9000)
#3.)
with self.assertRaises(TypeError, msg='TypeError: Descriptor and indices must be lists or strings.'):
test_aai_desc = test_pySAR.encode_aai_desc(descriptor=123)
test_aai_desc = test_pySAR.encode_aai_desc(indices=0.90)
test_aai_desc = test_pySAR.encode_aai_desc(descriptor=False)
test_aai_desc = test_pySAR.encode_aai_desc(indices=9000)
#4.)
test_aai_ = test_pySAR.encode_aai_desc(descriptors=desc_1, indices=aa_indices_1, spectrum='power')
self.assertIsInstance(test_aai_, pd.DataFrame, 'Output should be a DataFrame, got {}'.format(type(test_aai_)))
self.assertEqual(len(test_aai_), 8)
self.assertEqual(test_aai_.dtype, object)
def test_desc_encoding(self):
""" Testing Descriptor encoding functionality. """
desc_1 = "aa_comp"
desc_2 = "distribution"
desc_3 = "conjoint_triad"
desc_4 = ["moranauto", "quasi_seq_order"]
all_desc = [desc_1, desc_2, desc_3, desc_4]
error_desc = "blahblahblah"
error_desc_1 = 123
#1.)
test_pySAR = pysar.PySAR(config_file=self.all_config_files[0])
with self.assertRaises(ValueError, msg='ValueError: Descriptor parameter cannot be None.'):
test_desc = test_pySAR.encode_desc(descriptor=None)
with self.assertRaises(ValueError, msg='ValueError: Descriptor parameter cannot be None.'):
test_desc = test_pySAR.encode_desc(descriptor=error_desc)
with self.assertRaises(TypeError, msg='TypeError: Descriptor parameter has to be a strong or list.'):
test_desc = test_pySAR.encode_desc(descriptor=error_desc_1)
test_desc = test_pySAR.encode_desc(descriptor=123)
test_desc = test_pySAR.encode_desc(descriptor=0.90)
test_desc = test_pySAR.encode_desc(descriptor=False)
test_desc = test_pySAR.encode_desc(descriptor=9000)
#2.)
for de in range(0,len(all_desc)):
test_desc = test_pySAR.encode_desc(descriptor="aa_composition")
self.assertIsInstance(test_desc,pd.Series, 'Output should be a Series, got {}.'.format(type(test_desc)))
self.assertEqual(len(test_desc), 8)
self.assertEqual(test_desc.dtype, object)
def test_aai_encoding(self):
""" Testing AAI encoding functionality. """
aa_indices = ["CHAM810101","ISOY800103"]
aa_indices_1 = "NAKH920102"
aa_indices_2 = "LIFS790103"
aa_indices_3 = ["PTIO830101", "QIAN880136", "RACS820110"]
all_indices = [aa_indices, aa_indices_1, aa_indices_2, aa_indices_3]
error_aaindices = ["ABCD1234","ABCD12345"]
error_aaindices1 = "XYZ4567"
#test with erroneous indices
#1.)
test_pySAR = pysar.PySAR(config_file=self.all_config_files[0])
with self.assertRaises(ValueError, msg='ValueError: Indices parameter cannot be None.'):
test_aai_ = test_pySAR.encode_aai(indices=None)
#2.)
with self.assertRaises(ValueError, msg='ValueError: Indices parameter cannot be None.'):
test_aai_ = test_pySAR.encode_aai()
#3.)
with self.assertRaises(ValueError, msg='ValueError: Erroneous indices put into indices parameter.'):
test_aai_ = test_pySAR.encode_aai(indices=error_aaindices)
#4.)
with self.assertRaises(TypeError, msg='TypeError: Indices must be lists or strings.'):
test_aai = test_pySAR.encode_aai(indices=123)
test_aai = test_pySAR.encode_aai(indices=0.90)
test_aai = test_pySAR.encode_aai(indices=False)
test_aai = test_pySAR.encode_aai(indices=9000)
#5.)
for index in range(0, len(all_indices)):
test_aai_ = test_pySAR.encode_aai(indices=all_indices[index])
self.assertIsInstance(test_aai_, pd.Series, 'Output should be a Series, got {}'.format(type(test_aai_)))
self.assertEqual(len(test_aai_), 8)
self.assertEqual(test_aai_.dtype, object)
def test_get_activity(self):
""" Testing function that gets activity from dataset. """
#1.)
test_pySAR = pysar.PySAR(config_file=self.all_config_files[0])
activity = test_pySAR.get_activity()
self.assertEqual(activity.shape[0], test_pySAR.num_seqs,
'Shape of 1st dimension of Activity expected to be {} , got {} '.format(test_pySAR.num_seqs, activity.shape[0]))
self.assertEqual(activity.shape[1], 1,
'Shape of 2nd dimension of Activity expected to be 1, got {} '.format(activity.shape[1]))
self.assertIsInstance(activity, np.ndarray,
'Activity attribute should of type numpy array, got {}'.format(type(activity)))
self.assertTrue((activity[:10] == np.array(([55. ],[43. ],[49. ],[39.8],\
[52.9],[48.8],[45. ],[48.3],[61.5],[54.6]))).all())
#2.)
test_pySAR_2 = pysar.PySAR(config_file=self.all_config_files[1])
activity_2 = test_pySAR_2.get_activity()
self.assertEqual(activity_2.shape[0], test_pySAR_2.num_seqs,
'Shape of 1st dimension of Activity should be {} , got {} '.format(test_pySAR_2.num_seqs, activity_2.shape[0]))
self.assertEqual(activity_2.shape[1], 1,
'Shape of 2nd dimension of Activity should be 1, got {} '.format(activity.shape[1]))
self.assertIsInstance(activity_2, np.ndarray,
'Activity attribute should of type numpy array, got {}'.format(type(activity_2)))
# self.assertTrue((np.array(activity_2[0][0:3]) == np.array((-4.62693565,-5.59911039,-5.71578825))).all())
#3.)
test_pySAR_3 = pysar.PySAR(config_file=self.all_config_files[2])
activity_3 = test_pySAR_3.get_activity()
self.assertEqual(activity_3.shape[0], test_pySAR_3.num_seqs,
'Shape of 1st dimension of Activity should be {} , got {} '.format(test_pySAR_3.num_seqs, activity_3.shape[0]))
self.assertEqual(activity_3.shape[1], 1,
'Shape of 2nd dimension of Activity should be 1, got {} '.format(activity_3.shape[1]))
self.assertIsInstance(activity_3, np.ndarray,
'Activity attribute should of type numpy array, got {}'.format(type(activity_3)))
# self.assertTrue((activity_3[:10] == np.array(([55. ],[43. ],[49. ],[39.8],\
# [52.9],[48.8],[45. ],[48.3],[61.5],[54.6]))).all())
#4.)
test_pySAR_4 = pysar.PySAR(config_file=self.all_config_files[3])
activity_3 = test_pySAR_4.get_activity()
self.assertEqual(activity_3.shape[0], test_pySAR_4.num_seqs,
'Shape of 1st dimension of Activity should be {} , got {} '.format(test_pySAR_4.num_seqs, activity_3.shape[0]))
self.assertEqual(activity_3.shape[1], 1,
'Shape of 2nd dimension of Activity should be 1, got {} '.format(activity_3.shape[1]))
self.assertIsInstance(activity_3, np.ndarray,
'Activity attribute should of type numpy array, got {}'.format(type(activity_3)))
def test_pySAR(self):
""" Testing pySAR intialisation process and associated methods & attributes. """
test_pySAR = pysar.PySAR(config_file=self.all_config_files[0])
#1.)
#testing attribute values, including default values
self.assertEqual(test_pySAR.dataset, (os.path.join('tests', 'test_data', 'test_thermostability.txt')),
'Dataset attribute does not equal what was input, got {}.'.format(test_pySAR.dataset))
self.assertEqual(test_pySAR.sequence_col, "sequence",
'Sequence column attribute is not correct, got {}, expected {}.'.format(test_pySAR.sequence_col, "sequence"))
self.assertEqual(test_pySAR.activity, "T50",
"Activity attribute name not correct, expected {}, got {}.".format("T50", test_pySAR.activity))
self.assertEqual(test_pySAR.algorithm, "PLSRegression",
'Algorithm attribute not correct, expected {}, got {}.'.format("PLSRegression", test_pySAR.algorithm))
self.assertEqual(test_pySAR.test_split, 0.2,
'Test split not expected, got {}, expected {}.'.format(test_pySAR.test_split, 0.2))
self.assertIsNone(test_pySAR.aai_indices)
self.assertIsNone(test_pySAR.descriptors)
self.assertEqual(test_pySAR._parameters, {},
'Parameters attribute expected to be empty, got {}.'.format(test_pySAR.parameters))
self.assertIsInstance(test_pySAR.data, pd.DataFrame,
'Data expected to be a DataFrame, got {}.'.format(type(test_pySAR.data)))
self.assertEqual(test_pySAR.data.isnull().sum().sum(), 0,
'NAN/null values found in data dataframe')
self.assertEqual(test_pySAR.num_seqs, 261,
'Number of sequences expected to be 261, got {}.'.format(test_pySAR.num_seqs))
self.assertEqual(test_pySAR.seq_len, 466,
'Sequence length expected to be 466, got {}.'.format(test_pySAR.seq_len))
self.assertEqual((str(type(test_pySAR.model))), "<class 'pySAR.model.Model'>",
'Model class attribute expected to be an instance of the Model class, got {}.'.format((str(type(test_pySAR.model)))))
self.assertEqual(((type(test_pySAR.model.model).__name__)), "PLSRegression",
'Model type expected to be of type PLSRegression, got {}.'.format((type(test_pySAR.model.model).__name__)))
#2.)
#validate that if errorneous input parameters are input, that errors are raised
with self.assertRaises(OSError, msg='OS Error raised, config file not found.'):
test_pySAR1 = pysar.PySAR(config_file="blahblahblah")
with self.assertRaises(TypeError, msg='Type Error raised, config file parameter not correct data type.'):
test_pySAR2 = pysar.PySAR(config_file=101)